Item: THE INTERSECTION OF SCIENCE AND HUMAN BEHAVIOR IN TERRAIN MANAGEMENT: HOW SOCIAL MEDIA AND ARTIFICIAL INTELLIGENCE ARE CHANGING THE CULTURE
-
-
Title: THE INTERSECTION OF SCIENCE AND HUMAN BEHAVIOR IN TERRAIN MANAGEMENT: HOW SOCIAL MEDIA AND ARTIFICIAL INTELLIGENCE ARE CHANGING THE CULTURE
Proceedings: Proceedings, International Snow Science Workshop, Whistler, BC, Canada, 2026
Authors:
- Erme Catino [ Professional Instructor-American Avalanche Institute ] [ Backcountry Ski Guide, Teton Backcountry Guides ]
Date: 2026-09-28
Abstract: Technology, specifically regarding social media and Artificial Intelligence (Al), is moving at a speed we as society are struggling to keep up with and control. Backcountry skiing and riding is not immune to this phenomenon. A large proportion of backcountry skiers and riders today have moved from basing their tour plan decisions solely from the weather and avalanche forecast, to now incorporating these technological tools into their decision making. While social media (Facebook and Instagram) initially drove this change, applications such as Strava - most notably via their heat map function – and integrating AI into these applications, are changing people's behavior accessing the backcountry and evaluating terrain. This intersection of science and human behavior is superseding institutional knowledge, giving a false sense of conditions and hazards, and inadvertently opens terrain during periods of higher hazard. We have long observed the trickle-down effect of a slope opening in the field, attracting more skiers and riders based on tracks. However, backcountry users are now utilizing social media and heat maps to observe where others have traveled and are seemingly basing some decisions on such data points, regardless of the warnings of the local avalanche center and recent observations. The sheep mentality and social acceptance isn't new, and snow professionals regularly urge caution of this risk during periods of persistent weak layer avalanches. Utilizing a website that aggregates and intertwines Strava data with users' photos to create a snow condition report, I have been able to observe several examples of this. By investigating specific dates surrounding sensitive, persistent weak layer avalanche problems, I have collected chronological links demonstrating a relationship between people trusting the open-source data despite recent avalanches and/or forecast which contradicted the stability. Examples such as heat maps that show skin tracks going up the face of avalanche paths rather than traveling on the typical ridgelines, or users choosing terrain in the bullseye of recent avalanche activity without incident, which is then subsequently shared through this tool and attracts more users. While this is post-hoc analysis, there are several examples of backcountry user decision making that counter traditional warnings and forecasts, raising significant speculation about the role of such tools and their prevalence. Presenting this data and its inferences is purely to communicate the use of such technology and educate snow professionals on it, emphasizing the need to adapt to our audience. No shaming is intended in the analysis. This paper will begin to tackle the intersection of science and human behavior and address how AI generated data could influence human behavior in avalanche terrain. This is important for snow professionals and avalanche forecasters because we need to understand that our limitations are with our current tools and tactics in a changing technological environment and culture of backcountry users. As snow professionals we need to be aware and communicate to our audience before they get in trouble utilizing crowd sourced information during periods of higher hazard.
Object ID: ISSW2026_P4.20.pdf
DOI: https://doi.org/10.15788/1790099292
Language of Article: English
Presenter(s): Erme Catino
Keywords: Artificial Intelligence, Avalanche Education, Avalanche Forecasting, Decision Making, Risk Communication, Terrain
Page Number(s): 838 - 846
-